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人口流动与城市早期新冠肺炎疫情空间扩散及分布关系研究 被引量:7

A Research on the Relationship between Population Migration and Spatial Spread and Distribution of Early COVID-19 Epidemic
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摘要 分析全国340个城市早期新冠肺炎感染人数的时空分布,发现其符合地理邻近的基本规律。全域Moran’s I显示城市感染人数存在显著的空间依赖性,局域Moran’s I显示感染人数在空间上有典型的空间聚集性与异质性:“高高区”以湖北的城市为主,“高低区”围绕“高高区”分布,“高低区”以北京市为典型,“低低区”集中在西部。运用接收武汉流出人口数量排名前100城市的截面数据,经OLS和SLM、SEM等估计方法验证了人口流动与城市早期新冠肺炎确诊病例数空间分布的内在关联,再分别利用31个省/市/自治区和39个城市连续9天的面板数据模型进一步证实了这一结论的稳健性。建议短期内要持续管控人口流动,防止疫情扩散反弹,特别要注重境外输入性风险;长期则要完善重大疫情防控机制,正确认识人口流动对疫情防控的影响,切实维护好流动人口的合法权益。 By analyzing the spatiotemporal evolution of the number of newly diagnosed patients with new coronary pneumonia in 340 cities across the country,it is found that it conforms to the basic law of geographical proximity.Global Moran’s I analysis finds that the number of diagnosed patients with COVID-19 is spatial independent.Local Moran’s I analysis finds that the number of confirmed patients with new coronary pneumonia in cities across the country has typical spatial clustering and heterogeneity:the HH area is dominated by cities of Hubei Province;the LH area is distributed around the HH area;Beijing is typical of the HL area;the LL area is concentrated in the west.By using the cross-section data of the top 100 cities with the outflow population of Wuhan,and by OLS,SLM SEM and other estimation methods,the internal correlation between population flow and the spatial distribution of the confirmed COVID-19 cases in urban areas is verified,and the robustness of this conclusion is further confirmed by the panel data model of 39 cities of 31 provinces/municipalities/autonomous regions in 9 consecutive days.It is suggested that in the short term we should strengthen the temporary control measures for population movement to prevent the spread of the epidemic,and pay special attention to the risk of overseas immigration.In the long run,it is necessary to improve the major epidemic prevention and control systems and mechanisms,correctly understand the role of migration in epidemic prevention and control,and effectively safeguard the legitimate rights and interests of migrants.
作者 曾永明 骆泽平 杨敏 徐飞 ZENG Yongming;LUO Zeping;YANG Min;Xu Fei(School of Economics,Jiangxi University of Finance and Economics,Nanchang 330013,China;School of Humanities,Jiangxi University of Finance and Economics,Nanchang 330013,China)
出处 《人口与社会》 2020年第5期69-84,共16页 Population and Society
基金 江西省自然科学基金项目(20181BAA208020) 教育部人文社会科学基金项目(18YJC790006) 江西省教育厅科技项目(GJJ170355) 国家自然科学基金(72064018) 中国博士后基金特别资助项目(2018T110653) 中国博士后基金面上项目(2016M602080) 江西省社会科学基金(18SH13) 江西省高校人文社科基金。
关键词 新冠肺炎疫情 人口流动 疫情空间分布 地理迁徙大数据 COVID-19 population migration spread and distribution of the epidemic big data on geographic migration
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